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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 5 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
CN
2007
95views more  CN 2007»
13 years 4 months ago
Sampling large Internet topologies for simulation purposes
In this paper, we develop methods to ‘‘sample’’ a small realistic graph from a large Internet topology. Despite recent activity, modeling and generation of realistic graph...
Vaishnavi Krishnamurthy, Michalis Faloutsos, Marek...
INFOCOM
2006
IEEE
13 years 10 months ago
Sampling Techniques for Large, Dynamic Graphs
— Peer-to-peer systems are becoming increasingly popular, with millions of simultaneous users and a wide range of applications. Understanding existing systems and devising new pe...
Daniel Stutzbach, Reza Rejaie, Nick G. Duffield, S...
ICDM
2008
IEEE
106views Data Mining» more  ICDM 2008»
13 years 11 months ago
Metropolis Algorithms for Representative Subgraph Sampling
While data mining in chemoinformatics studied graph data with dozens of nodes, systems biology and the Internet are now generating graph data with thousands and millions of nodes....
Christian Hübler, Hans-Peter Kriegel, Karsten...
INFOCOM
2012
IEEE
11 years 7 months ago
Sampling directed graphs with random walks
Abstract—Despite recent efforts to characterize complex networks such as citation graphs or online social networks (OSNs), little attention has been given to developing tools tha...
Bruno F. Ribeiro, Pinghui Wang, Fabricio Murai, Do...